07/12/2015

I have been working on a new exhibition, hopefully in Berlin. For now I haven't found a place neither what I will show. But I have been experimenting, working on my images. Below is an example of the kind of visuals I want to produce, you have to keep in mind those images almost 1m by 1m big.

I'm not sure if all the images are interesting, but I like the contrast between the first on the top and the last one in the bottom.

I'm not sure neither about the color I used to frame each little planet version in that illustration. But if you are interested in knowing it's fuchsia.

30/11/2015

I can do Python, I can do data analysis (stats, modeling, machine learning, analytic and so on), I can do data visualization, I can learn fast, I can create, I can communicate, I can translate (or report information to different departments), I can write, I can connect people, I can invest myself a lot, I can team play. Basically I can do a lot and I want to do a lot. I also run pretty fast.

What I can't do is to come with miracle solutions to every problems before knowing the problems... Or it's pure luck and I should really start playing lottery then.

I already wrote about this area, but the density of interesting spots
in that tiny street now surrounded by a polished touristy area is
amazing. There is always something to discover, be it a gallery and
bookshop neurotitan or the Kino Central (check the Kino Central article). And that’s not all! The bar Eschscloraque is a kind of gravity center that keep all the places together.

Eschchloraque did celebrate its 20-year anniversary this summer 2015
and its art activity is still swarming. The bar is obviously not only a
bar; there is a stage and regular concerts, shows and performances. A
kind of place where opera singers, cabaret freak shows, musicians and
dancers can be on stage. About dance, the series of events Band à Part takes over the place regularly on late

Tuesday evenings and it’s always interesting.
Again about the place, it looks rusty, dark, made with steel pieces. I
don’t know if this is something typical about this city, but it always
make me think of Berlin as a giant spacecraft waiting to take off again.
I love it.

24/11/2015

I had the chance to attend the Data Natives 2015 event last week in Berlin. A first time event having for topics FinTech, IoT and of course Big Data. I heard some interesting talks but also less interesting ones. You can still hear people having the dream of forecasting anything with the help of more data, but with often the feeling it's only in order to sale more stuffs. I haven't got the life improvement that suppose to go with Big Data (e.g. mass surveillance doesn't work obviously).

But here and there you can sometimes hear someone talking about a project that hold your attention. For me the most interesting aspect is the inter-disciplinary or multi-disciplinary aspect of the data. To achieve something relevant or meaningful with all the available information, you need to be able to define first what is the problem you are trying to solve (and yes I have a degree in opening open door).

Four presentations are still in my head, one using NLP to pre-sort a lot of CV (from HitFox during the first day of the program) and a second using computer vision to automatically give feedback on webpage design (from EyeQuant last talk of the second day). Actually for the last one their talk was much wider than this single problem.

About IoT and FinTech is wasn't really impressive. Actually the only striking aspect is that the same tools are used whatever is your field of work (like data science / analytic / finance): you accumulate data, you trying to find information and pattern into them, this in order to derive model to make prediction. And without surprises the most interesting talks about FinTech came from the people involved in the Bitcoin economy / technology (Blockchain and ascribe Gmbh). Maybe the banks have some cool stuffs to talk about, but they weren't really present.

02/11/2015

I'm interested in knowing, observing how my field - applied research, technology, imaging, innovation... whatever you call it - is evolving. Working full time on one project is of course a good solution to see what's going on, but it's also taking the risk of being stock in daily routines. In that sens it's always wise to have a look of what your neighbors, competitors are doing, how they try to solve the same problem you are working on.

From my own experience I know that we - let's call us/me applied/data scientist - are very fast categorized in sub-fields, as experts and that it is sometimes difficult to extract yourself from the prism of how people are perceiving what you can do. Having said that, to be able to attend events, meet a new crowd, hopefully interesting people, exchange information, re-present yourself, feel how an industry is growing is something vital.

A few days ago I did spot an event Data Natives 2015 scheduled in Berlin the coming 19-20 of November. The keywords combination used to introduce the program is almost too perfect: IoT (internet of thing), FinTech (Financial Technology and not tech from Finland which sounds pretty cool too) and Big Data of course. Needless to say that I'm pretty excited to attend this conference!

01/11/2015

A weekend including Halloween over Friday and Saturday, the guarantee to witness how mainstream we all went, but there is hope, I hope.

Friday evening at a checkpoint
I'm sick this week, no sport, keep calm and have some rest said the doctor. But it's Friday evening and I want to move and see what is happening outside. I heard there is a traditional alleycat around Halloween and decided to stay at one of the checkpoint, one appears to be at the cicli-berlinetta bike shop - probably the best bike shop in Berlin - about 800m from our place.

For the occasion the entrance of the shop was turned into a photo studio, each participant was taken into picture before rolling some dices and jumping almost immediately again on their bike to their next check point. Basically people - the bike messengers - playing a game being what they usually do by day for living. Why will you ask? Why not will I answer and people seem to have fun.

It was not my first time hanging around after the closing time of the shop - and by the way the shop online never stop. Always interesting bike fellows to meet and talk to. A ratio of one nationality per person, English, German and more languages spoken with various accents. I love that. Always interesting to hear the story behind the people - by people I meant mostly bike messengers - and the relationship with the streets. Something I like while being on my bike - or my roller skates back in the days in Paris - is to move faster than the pedestrians, sometimes faster than the cars and to observe the city, the multiple interactions at each street corners.

Saturday evening counting the pumpkins
Still sick, always a good excuse to not go out. Only expedition I did was to attend a pre-party in Schöneberg. I crossed the city, avoid a taxi - by that I meant I had to stop or being rolled over by taxi while driving at the green light in the bike lane - reach the place, had a tea, two snaps and I let my friends sheep-ing or penguin-ing the rest of the night - by that I meant behaving like sheep and/or penguins and do like everybody else like going to a costume party tonight.

Berlin is a place where you can go out and get good music all the time, Halloween should a night where you do nothing.

It's 11:00pm and I jump on my red bike - not because of the dress code of the night, my bike is always red - and hit toward Prenzlauerberg following another way. Nollendorf Platz is quiet, nothing special is happening.

Passing behind Potsdamer Platz I see my first accident: three cars and bus trying to compress themselves into one art pieces, nobody seem to be injured except the cars, losers.

I keep going and enter the Hannah-Arendt street. Parallel to Unter del Linden you are mostly alone by night in that street, the city looks like a zombie spot and you will not be surprised to see some at each corner.

Then it's Alexander Platz. I like this place, tonight the police is there and a lot of lost people as well, some going to Halloween party. I see a lot of witches, skulls faces, zombie nurses, group of cats - more the pajamas costume than the slutty version - nothing very original.

I passed U-Rosa Luxemburg Platz and start Schönhauser Allee. First bar is the gothic Lost or Last Cathedral where it seems people having a casual dress code evening. Getting closer to U-Eberwalderdstrasse and the Ferdinand club where only ugly locals are going I see my second car accident. Always funny to see people in costume looking at they cars into each other, hopefully nobody is hurt, just the cars.

25/10/2015

Context
In a previous post I talked about the last event in my field I did attend. Now I want to talk about my perception of this domain which is called color science. I'm pretty sure it can be applied to other fields of research as well.

From the first time I joined this community, from article reader, article contributor to reviewer, committee member and session chair my understanding of what is color science has evolved. One important thing is to stay humble, especially with the new comers. I have been one them, it was impressive. Impressive because you meet the people, authors of research articles that are part of the foundation of you work. You can add a person, a voice to written words, it's actually pretty cool.

There aren't thousand concepts to understand/enter the world of color science. Like in every fields it's about observation and trying to explain what's happening. But here it's all about light - its spectral properties - how we perceive this signal - a single light source to an image in the visible spectrum - and how can we develop robust scientific/engineering "stuffs" around it. What I find interesting is to witness what is the new thing coming each year, how a technical improvement can open a door for further applications.

Color trends
Among the research sub-fields presented at CIC this year I want to come back on four of them.

There is the recurrent discussion about color metrics, from a purely mathematical/geometrical approach to a more perception-wise approach trying to add an average human appreciation of the difference between two signals. Having a good metric is always helpful to evaluate your algorithm/experiment. Over the years the metrics are evolving, context is important (from display calibration to color textile differences...).

There is the what I call "purely geometrical approach" discussion where having a signal as vector of n values - for n wavelength - a group of sensors - basic configuration made of three basis like RGB basis - you want to know the value of this signal once projected on the known basis/sensors. From that you can jump into optimization, addressing various problems such as finding the scene illuminant/white point, study metamerism. It seems obvious but it's not.

There is printing and 3D printing - there I meant color 3D printing. Just think of how to design a color test-chart for such printing system. HDR display is also coming stronger than ever. What is interesting with these two examples is that they both require to know your workflow, they are the "end" of a process chain: you need to understand the acquisition process to do a good reproduction. Understanding the use of the technology is obviously required.

On the last paragraph one can add the understanding of gamut mapping and how you "move" into your color space as something very important. For printers you have multi-inks system changing the shape of the color space available. For high resolution TV and HDR screen the color gamut shape may not change a lot - almost - but the variability of screen size, intensity scale, technology available make it difficult - to be understood as something cool and challenging for me - to offer a comfortable experience to the user among the different platforms.

Now that I'm a bit more in control with the tools/concepts in my field and sub-fields I have the tendency to prefer the projects combining several concepts - like high quality printing and movie post-production - and I always appreciate to hear how the authors are presenting their projects, which story they are telling us.

23/10/2015

What is CIC you may ask yourself? It's stand for Color Imaging Conference, a conference about color and imaging. This year it took place in Darmstadt DE. The last 22 editions always took place in the US, last year it was in Boston MA, two years ago in Albuquerque NM, three years ago in Los Angeles CA, four years ago in San Antonio TX and that's it for my involvement. Next stop is San Diego CA in November 2016.

I'm a regular attendee, I joined this community already ten years ago alternating between CGIV, AIC, EI and CIC. Depending of the event you will meet a slightly different crowd or so to say different crowds will meet allowing to go deeper in the various fields represented. But for sure it's about imaging, color, perception, printing, archiving, image acquisition, color management, camera and display calibration, gamut mapping and more.

This year almost 200 persons were attending the event in Darmstadt. There is a kind of routine in such event and being part of the committee allows you to see the people interaction with a special look. It's very special to see the attendees - former colleagues, friends, known members of this community - arriving from everywhere almost - from North America, Europe, Asia, Australia... - and being all jet-lagged. Even if you are traveling in the same time zone you will end up jet-lagged. First of all the schedule is tide and you have to use the "free" time to talk with everybody. Sharing a meal or a beer is usually very appropriate. As a result you barely have time to rest, but the kind of adrenaline you get from meeting the crème de la crème of the color scientists keeps you awake.

06/10/2015

I joined yesterday evening another Meetup hosted by Bayer in Berlin. A master class about PR in the digital age given by Andreas Winiarski from RCKT & Rocket Internet. Why attending this event you may ask? First of all I heard about of the mini burgers legend that are possibly served during the Meetup organized at this location... No burgers this time but mini flammkuchen, so that wasn't too bad. Secondly and more seriously I was curious to hear a PR person talking about his work and experience. I'm not one of them - I'm a data scientist with a liking for computer vision and color science - but in my work, at some point, I may have to communicate with the communicating people.

What I like about the talk was the way - it seems - this profession has changed putting the people more in control by taking control of the available tools: you are the first communicator. You don't need much of infrastructure to start spreading your voice as you are always two clicks away from starting a blog.

I also appreciate the position of the speaker - and I guess the one of the company he is representing - regarding where they want to go, what they want to achieve. The internet is not only reserved to the US or China. Germany and Europe have to be part the game. There is no local market, everything is global from the beginning and the model followed by Rocket Internet is completely going in that direction.

To be short that was a pretty interesting presentation. I can't say I learned many new things, but it's nice to see some of your thoughts formalized by others. It make you feel that you are not completely disconnected from the world.

30/09/2015

Last evening I did attend a joined Meetup from the Python User Berlin (PUB) and the Zalando Tech Event hosted by Zalando and offering talks on Natural Langage Processing (NLP). Both talks went well and gave two views on the topic: one on the state of the art of the tools for NLP using Python and a second more applied.

The discussions I add after while enjoying a club mate - la boisson des champions - were equally interesting. First of all I started discussing with a expert of NLP trying to explain why I joined this event and what was my link with NLP. In my very recent job experience at EyeEm I just touched the surface of NLP preparing data for Machine Learning (ML) using nltk together with WordNet, ImageNet. Actually I didn't do much of text analysis but batching word definition. In that experiment the text analysis will have come after this step and that's where semantic is jumping into the discussion. Because working with the word dictionary is one side of the problem: you have one word with its definition and often - at least with scientists or engineers - you are in the inverse configuration which is you having words when actually you want to extract a definition, an idea, an information... And I let you google automatic image tagging, deep learning.

After exchanging ideas and experiences about NLP I did continue seeping the offered mate with one Zalando employee. I was curious - as usual - to understand what it means to be a data scientist here. Because if the definition is very general - a data scientist works with data, we are not expert - it's interesting to see how many fields we - I'm one of those people - cover in our daily work. Using the same language - e.g. Python - we can go from signal processing, computer vision, image retrieval, NLP, how to deal with Databases - a year ago I wrote on the topic Databases and natural Langage graphs en stock - how to present your results to non expert by doing nice visualization and many more... So if we are not expert we need to be pretty fast I acquiring skills from various fields and/or use the appropriate tools.

16/09/2015

Following my first exhibition of little planet pictures back in June in Morlaix - it's in Bretany - I did open a shop in Etsy a few days ago. The shop is called JeremieLittlePlanets for two reasons: one my name is Jérémie and secondly it is about my little planets images.

Have a look to the shop, like it if you like it, share it and even order images if you like them very much, they are great gift I heard.

Each images have been printed 5 times, 3 in 70x70cm and 7 in 40x40cm. Each copy is signed and numbered. Some of them have found lucky buyers, mostly in France until now in Paris, Nantes and Morlaix. But my images can't wait to travel more.

The selection of images we presented last June together with my friend Laurent from feelsen are the memories of time I had the last years in Berlin, Paris, Marseille, Szczecin, Polish coast, Reunion island forest, South of France...

Why?
Why not will I answer. Even so I do jog regularly, I didn't have the idea - at the beginning of my numerous attempt to have a sporty life - to make one day such a long run. But here is the thing, you go jogging a bit, two-three times a week, the body gets used to it, the head follows and has some pleasure doing it, it goes step by step. The 10km barrier is crossed since a few months without being tired, for the same training time a longer distance is reached. A new level will be taken soon.

While we were having an amazing spotter weekend in Amsterdam last October, many people did realize jogging was an activity shared by many of us. But we do live in different cities and we can't go jogging together every weekend... Running a marathon, some of us did it already and obviously the wish to do it was in some of us.

Fun-fact-number-one, if you tell someone you are running regularly he/she will almost instantly add "for a marathon?" and answer no will ends up the discussion.

Following the spotter weekend, someone - we will cal him Martin - propose to join the force and to register to marathon. Destinations were proposed and Vilnius won. Lithuania it will be! I'm just coming back from it, lights in my eyes and stiffness everywhere else.

Fun-fact-number-two, tell someone you are going to run a marathon and he/she will reply "an half-marathon, a real marathon?" just checking if...

A bit before the run
The run is in Vinius, capital of Lithuania. To reach my destination I first land in Riga where I met one of the spotter bosses - we will call him Bart - and a traveling foody expert/instafood addicted - we will call her Gol. From the capital of Latvia we jump into a bus aiming for Vilnius. It's Friday evening, run is on Sunday. Wonderful welcome of the locals, it's difficult to do it better!

During the run
Two loops only are scheduled, but each loop has 21km. Grouped start for the half-marathon and marathon. The first round is going according to plan for me, not too fast/slow, a good 10km/h pace.

The arrival line is crossed for the first time letting the road empty in front of us. We were a few thousand two hours ago, now only the marathon runners stay in the race. We left again the city center, less people to encourage us but more space and flatter road.

Then I start to feel a little pain in my right knee. Bad luck. The remains of a twisted ankle while playing beach volley-ball a month ago. I need to slow down, to be more careful how I land my foot, but after two hours your legs are getting heavy and it's difficult to control everything. Luckily it's the time I meet a Lucas with whom I run for a few kms. We enter the big park, jog into the forest and the soon cross the sign 28km, the longest distance ever ran for me. Cool! But there is still 14km to do...

From there I continue alone letting my partner at his speed. I need to stop sometimes, to do some stretching exercises, sometimes walk a bit and start again. I'm not completely alone, the remaining runners around me are pretty much like me running/walking/making faces. We recognize each other, smiling to each other. The 36km sign is passed and the rest of the path is crossing the old town, it looks nice but the road sucks, full of up and down and ugly pavement...

Now it starts to be difficult really, the legs are super heavy and sometimes don't even want to walk. In the last going down slope I can't relax my body, but the 40km have been reached! Then 41km and gathering my last energy I can finish the last 500m running for real in pain. The spotters cheerleaders are there! And the non-alcoholic beer you get at the arrival is the best drink on earth!

I go back limping with Martin to our hostel. On our way we have to time to cheer one Bart followed by one Sarunas in the 10km race, go go go! A Martin full of lights in his eyes and me thinking of my new training. Basically I need to do more long distance training, improve my technique, learn to jog/eat and digest, in the same time, fix my knee... There is room for improvement.

What a day! My flight to Berlin is taking of from Riga tomorrow, so I need to reach this city in time. We - two Bulgarians and me - are joining Anete which is driving back to Riga - one of the Latvian spotter in Riga, of the marathon runners and spotters the youngest, the most discrete, the fastest and the most experimented of us. It's always good to practice a sport with stronger than you, to share experience, it's only motivation for the next run.

08/09/2015

I finally managed to attend the Shadow ML - for Machine Learning - meetup in Berlin yesterday evening, hosted by Amazon in their Computer Vision division in Berlin. Two talks were scheduled, one with images and a second with words. I explain.

Before pizza time
Here we learn about soft shadow removing. I liked this talk because it combined computer vision (CV) and machine learning (ML) and it's a problem I'm aware of as I'm regularly facing it when I'm post-processing my spherical panorama pictures taken under the sun - you can see my shadow in the picture.

What I remember from the hard shadow problem description is that a big part of the solution is to be able to isolate in the picture the shadow areas. What is a shadow area you may wonder? It's a part - or parts - of an image where the brightness has been drastically reduced such that they appear almost grey but there is still some color information available. Saying that we almost solve our problem: we need to find the color information in the shadow area and adjust its brightness to match the non shadowed neighbor area. You may have to operate in a different color space than RGB to keep the chromatic information undamaged and to change only the pixel brightness/luminance. A good image segmentation is an inevitable step.

For hard shadow the segmentation is an "easy" task as the transition between shadow/not-shadow areas is fast/brutal, in another word not soft. The problem with the soft transition is that is required a lot of human inputs to mask the image - in the sens of creating a mask that isolate the shadow areas from the others - and we want to automate this task.

A solution proposed yesterday was to use machine learning in order to make your system learning about the difference image with and without shadow. The speaker talked about the problem of getting data - which is a recurrent part of machine learning problem modelisation and any other scientific problems - and how he did create his data-set: computer generated images with Maya where he could get two sets, one with shadow and another without for the same scene.

After that I got a bit lost of on what the author does when he found out where the shadow areas were. But assuming the areas have been well discriminated you still need to adjust the brightness level. From that two solutions at least: if the area is homogeneous then a simple scaling factor/function should do something, treating the background - or the area - as a texture can be helpful too especially if you plan is to use in-painting techniques. But the chosen solution is of course linked to what you want to do: preserving information in the image - then I will say no in-painting - or tricking the eye/human brain such that the image appears nice without shadows - then go for in-painting.

After pizza time
A complete different topic to follow but not less interesting. It was about text and word analysis. For an introduction you can check WordNet to have a glimpse of what that field is. But back to the second speaker, his problem was to see if we can predict an affiliation to a political party based on text analysis.

As the speaker did mention it this is/was a work in progress where the first task was to establish a usable data-set for building the classifier. The text of each party manifesto was employed for that purpose.
Once you have your classifier what you want is to evaluate it. All the interventions, talks given by the government members, parliament members are the perfect data sources to be used for that as well article from different newspapers could be feed to the system.

This work goes as well into the direction of sentiment analysis and a temporal parameter is something you want to have in such problem. Depending of who is running the country, who has the majority at the parliament the roles, the words play/use by the people representatives evolve. It might be obvious but this kind of tool can tell us how much we perceive the words, talks given by our politicians and how much they or we interpret/dream/hallucinate about different situations.

Building such system wasn't too complicated - if I got it right from the speaker(s) - and the main challenges were/are to get clean data. As for all machine learning you need clean data, in every basic or applied research actually.

30/08/2015

When the thermometer get an heatstroke it's nice to be able to jump into the water. Luckily Berlin is surrounded by lakes and other Fribäder [https://www.berlin.de/special/sport-und-fitness/schwimmen/schwimmbad/kategorie/freibad/﻿] within a reasonable travel distance by bike and/or public transport. If the lakes are easy to reach, they are some efforts to provide to get places, water quality and sun or shadow. A short review of my last visits below.

Teufelsee

Water so so, small

A big sausage fest

not much sun

but view on Teufelberg

Schlachtensse

Relatively big, a mix of locals, families and people coming from far. As you walk away from the U-Bahn you get more easily a tiny spot. Plus you can jog around and the path is almost exactly 5km.

No naked people, water is not transparent but quality ok. Getting less full as the evening comes, leaving only families and a nice atmosphere.

Liepnitzsee

The best, only the best.

You have to deserve it and cycle a lot even when doing a part by S-bahn.

Superb water quality, beautiful green color. There is an island!!! There is bier garten on the island

There is a tiny lovely ferry!!! They are fkk people, but on the island they aren't so ugly.

As the other lakes there are not boats with engines, making it safe to swim. And I recall, the water quality is great. So a bit if an expedition but worth it.

24/06/2015

My last post on the SpottedByLocals blog is called Chez Michel, full text on the link and below. I let you discover it. And long story short it's a nice place.

Chez Michel

Discussions about food with me are endless. Not because I’m French
and that I’m supposed to know about food in general. But there is a
great chance that topic comes up after just the first few words with a
new acquaintance. Especially if you are a foreigner in a foreign country
like me. Often I can’t answer the question “where is the best French
restaurant in Berlin?”. It’s just that I’m interested in food in
general, when it’s good it’s good.

After years of travelling I learned how to cook recipes that please
my taste buds with the ingredients I can find where I live. And it’s
very seldom that I can recreate a taste I remember, especially family
recipes as there are so many parameters more than just the ingredients.
You may need the sound of the wind in the trees, the smell of the bbq or
the voice of your grandmother telling you to stop playing football and
to come eat.

Therefore I was happily surprised when I joined friends in the
restaurant Chez Michel. Here I found a simple kitchen, authentic, a menu
full of classics from boudin to quiche and amazing pies. Amazing
because they taste as if there were just leaving the oven in the family
kitchen I grew up in. I can’t wait to go back!

21/06/2015

For the first stage we were two and the at the end of the tour we were four. It's usually the other way around with bike tour, you loose people on the way. Not this time.

The pitch
A few month ago when the days started to get longer and the weather warmer - in theory only - the need to jump on your bike and to explore the city or to go away from it is getting bigger. An idea that come regularly at the same period of the year is "why don't we do the Mauerweg"? What is it you will ask, it's simple I will answer, there is a path you can follow which follows the former path of the Berliner wall. And no it's not only the East-Side gallery or the short version you can do in a group following a guy wearing a yellow t-shirt Mauerweg. It's about 170km.

The Berlin wall path forms a loop, it divides the city and actually surrounds West-Berlin. So when you do the Mauerweg you actually doing a tour all around former West-Berlin. The most impressive part is maybe the one in the city because we are full of images of the wall being built, houses destroyed, we think we know. The almost 120km other km are also very interesting. It gives an idea of the Berlin size, you relation to the city changes. As often - at least to me - to know where I'm, where I go, what's the space I'm spanning is of great help to feel in control. It's probably why I like so much maps.

As the first half I did some weeks ago, this time we did not see remaining of the wall - actually only two pieces close the Schweinmuseum, true story. I can understand the desire to remove this sign visible. But it's also important to not forget. In that matter there is regularly small texts, explanations in the middle of the forest or just a picture of one or two men. Just to remind you that some years ago, wanted to cross the wall could be deadly. Telling history by the mean of bringing local memories to you is something you can easily relate to.

But let's back to the tour and its second stage Wannsee to Mauerpark for 75ish km

11:30am the fours cyclists are all in Alexander Platz waiting for their Regio toward Potsdam. 15min later we are in S-Wannsee ready to rumble in the Brandenburg jungle.

The first 10km almost bring you back to Wannsee, but before you go along the water, you pass the Pfaueninsel and continue to the famous spy exchange bridge also called Glienicker bridge. The following part passing by Potsdam Griebnitzsee is lovely, all house are beautiful and massive and you may consider to settle some years right there. But the stage isn't over so we continue.

We enter the forest, escaping it only to cross the highway and to observe the former Zoll station which looks impressive. A place you don't want to spend your vacation. You continue, along a canal for while, recognising many names of last subway station lines. You may surprised yourself saying loud "haaaa it's here, hmmmm, yeah it's far".

After Lichtenrade and passing Rudow you enter an area in big changes. The "new new" aiport which should open one day is getting reached by the city and the mix between houses and fields with and without animals is more diffuse. In a few word it's not the most interesting part. But if you want to ride your bike fast there is a track going almost from the airport to Baumschulenweg in a long straight line.

We had a nice stop in an imbiss located in the garden of an house. Sitting there the time stopped, we did enjoy our beers and French fries with some Schlager coming from the garden. And we had time to see people. People and many dogs. The more you go away from the city center the more the typical couple you will meet is a human being and a dog. I have the same experience every time I go jogging toward Pankow and norther.

The entrance in the "alive" Berlin is fast and brutal as we forgot about the fête de la musique. We skipped the Mauerwerg path towards Görlitzer Part as we all knew it already to end in a nice beer garden but also cinema but also local brewery. Once again the time stopped. It was a super nice bike trip, crossing so many different areas, different people, different images in our heads.

8:22ish pm and we are home. Anne-Laure and me continue the tour to our place, leaving Steffen and Alexander near Ostkreuz. It's time now to have some rest or to collapse.

I do visit frequently vernissages, mostly in Berlin where I live - like earlier tonight I went to the project space tête - often because friends invite me, sometimes they show their work, sometimes for no reasons but rarely to show my work. I'm not really an artist, I'm like many of you, I do several things which can't be defined by one word only, anyway... That's what did happen a week ago Friday 5th of June 2015. Not in Berlin but in the city Morlaix in Britannia.

Before the vernissage
Since a little while I had the desire to show my images by other means than by creating web pages or privately. More preciasely my "little planets" images. I do receive regularly positive comments about these images from my world wide connected friends. I thought I could try to reach another public, an audience I don't know personnaly.

Following a simple post on Facebook about two three months ago, Laurent - a long time friend because we were in the same class all along our high-school time in Paris - offered me to host an exhibition at his agency. In two seconds it was decided to organize my first exhibition in Morlaix located deep in Brittany, something like 1500km from Berlin.

Many e-mails, audio and video conferences on Skype later and the official vernissage date was getting closer... What can I say? It was pretty cool to see all the process behind the organization of an art exhibition. The choice of what to show, how to present the images, how to explain, how to put words on images, how to present myself, which frames style? what prices? and will people come?

To choose images over the phone is a challenge, to discover them hours before the opening a surprise. For me a good surprise, my art dealer and his assistant had to re-print everything just before I came... they had all under control!

During the vernissage
First time, some known family faces coming especially from Paris! Locals completely unknown to me. A lot of finger food, cider, it can start.

The choice of images - this process took several weeks and we opted for 10
that illustrate the best what I can do - worked well. About thirty visitors came. People were curious, weren't scared to talk with me. And more important they were reacting to the images.

After the vernissage
Now I'm back in Berlin. The images will stay in the gallery until middle of July. I hope more people will be able to experience them, who knows maybe even buy one?

And now I have many things to do, ideas to develop, images to print, to find new place where to exhibit my work. Hoping this wasn't my last exhibition.

27/05/2015

The holly Grail of the day
Build an interactive data
visualization of my own networks where I could jump from one network to
the other and navigate in time.On the paper it sounds easy: use your own network data (facebook (FB), linkedin (LI), twitter, instagram, EyeEm...) to exercise yourself on social graph. In other words use tools from your beloved statistic toolbox (Matlab, Python, R...).

The why
Why, why and why using your own data? First reason and obvious to me, you know the data - or at least part of it - and it should be bit easier to navigate through them. About the first why bother to do that? Once again it's simple and the answer is curiosity. The more people use a buzz word in all conversations the less they understand what it means and I don't like to not understand.

Social graphs are interesting because they illustrate part of our multiple identities - this of course if you decided to look at your own network instead of looking at the interaction between people forming a group which is also interesting (data journalism loves to dissect political social network to find out who are the leaders). We don't know the same people/don't play the same character depending of the network as they describe different interactions (e.g. FB vs LI).

The reverse engineer path
The path I did follow wasn't probably the most efficient but I'm getting better every day. Plotting a social graph isn't the most difficult task. Using gephi you can relatively fast generate beautiful graphs. In parallel I took in statistic and social network analysis to refresh parts of my brain on the topic.

The prototype
As inmaps isn't available any moreI ended up on another automatic solution called socilab.con that requires you to log with your linkedin account. It's nicely made, you get a graph and several score values that describe your network and which role you play in it. Sadly it is limited to 500 contacts, so if your contact list is much bigger the analysis is incomplete. But this website allows you to download this version of your contact list. And actually what you are downloading is the formatted data from your LI account under the form of an adjacency matrix. I had to clean a bit the data using Python and Pandas which make any manipulation of csv file a real pleasure.

The adjacency matrix
This matrix - if I understood correctly - should be squarewhere both columns and rows have the same names: your contact name list. Depending of the cell value 0 or 1 you know if your contact know each other or not, the matrix isn't symmetric. It's a particular case of data, because if you look at a FB group of people liking peanut butter toast for diner they may not know each other but they are all connected by their irrational attraction to fatty cream and low safe consideration.

Where the trouble starts
It starts right when you want to access your data... Building by hand this matrix is doable but is a really silly task.And both LI and FB do make the task easy neither. You will need to play with their API (I haven't checked for twitter, instagram and more yet) to access your account and download/build your matrix.

24/05/2015

Four
people signed up, but one decided to sleep all day long and another did
prefer to drink Caipirinha at the Karnaval der Kulturen happening the
same weekend... Only two braves and their bike on the departure line!

A
few km later we are in the pampa. The time to leave the city, to be
still between East and West and to reach a border to the nature. We go
over Tegel, Hohen Neundorf, Henningsdorf, aiming for Spandau but always
staying away from it.

Relatively fast it's 50km on our counter. Down Spandau - I know the part because of previous summer expedition in this area looking for lakes to swim - the way is going in the forest again and is passing Sacrower See just after the Gross Glienicker See which happen to have been crossed by the wall delimitation.

From
that point is becoming a bit tricky. If you do want to follow the real
Mauer path you have to take a boat to reach the Glienicker bridge... So
instead the indicated way is to go to Kladow which is facing S-Wannsee.
There is one of the public transport ferry lines. It's a big boat,
there is place of at least 50bikes. But it's a nice day, no way we can
get in without waiting hours.

6:03pm there is
only one thing we can do while brainstorming how to go to back to
Berlin: drinking beers and eating sausages in one of the beer gardens.
Either we go to Potsdam and from there jump into the S-Bahn, but it
means 20km more or we go back to Spandau by another way and following
the water. We choose the second option which only 12 km to the daily ride.

Going back
North we made another stop in Gatow where a fair is taking place. This
time no sausages but delicious spätzle with cheese and beer of course.
Our stomach feeling satisfied we continue and somehow ends up in the
S-Bahn station Streesow.9:33pm the sun is going down. A lot of km in our legs. It's nice to be transported by the outdoor S-Bahn that slowly brings us back to civilisation.
I go down at S-Friedrich Strasse and cycle a few hundred meters to meet
another friend for a last beer in this lovely summer evening.

22/05/2015

First Zalendo Tech Event at their Tech HQ nearby Alexanderplatz yesterday evening. To open their series of Meetup event Zalendo invited Professor Sepp Hochreiter of Johannes Kepler University in Linz to talk about deep learning.

attentive crowd

About the talkThe talk was good but not adapted to an academic audience. If you are familiar with the topic you probably wouldn't have learned something new. But the talk did lead to interesting - and often expected - questions around and about deep learning. Sadly - to me - it was more where does it work?, what are the best parameters? than how does it work actually?

As the speaker did remind to us, neural networks (NNs) aren't new on the market. They were discoveries years ago, it was promising and then nothing, other techniques were used, leaving specialists in their niche. I do remember courses during my master in image processing about 15 years ago [in Pierre et Marie Curie Paris VI] where the person teaching and introducing KNN and NNs sounds both excited and disenchanted. This until computers got faster (thanks to cpu, gpu, many-core, cluster, graphic card programming "et j'en passe") and suddenly it was possible to use NNs, to get results, to reproduce them and to beat classification challenges by far comparing to the expert of the field.

For every new promising technique there is the temptation to use if for everything in a brute force manner. But it doesn't work all the time. One remark given by the speaker is these solutions work when you are overloaded with data, when you immersed into data. It's not a surprise that big players such as Google, Facebook, Amazon and more are heavy on growing their deep learning team.

About automation, AIand drugsYou hear and see more and more presentations about deep learning, artificial intelligence (AI) where people are dreaming of AI being able to put words on a given image in a similar way a human will do. It's kind of working but there is no magic. It made me remember about an experiment where the researchers claimed to be able to produce images/video corresponding to the images we see in our dreams. Often people fear - and they can - about computer taking control over us, making decisions for us until we start working for them.It is interesting to understand why pharmacy companies - those making drugs - are so big into deep learning. Bio-Informatics offer the perfect environment for developing big data solution. Here I'm not talking about the phase where drug need to be tested and evaluated on human but what happen before. Biology and chemistry (or computer chemistry) can be simulated using pretty accurate models, meaning you don't need to run an actual biological or chemical experiment. You can simulate the experiment, generate a huge amount of data and let your algorithm do the analysis. And guess what, computer vision, machine learning, deep learning - not to mention optimization - are part of the solution. And the faster you get your results, the faster you have a new drug to potentially introduce on the market hopefully before your competitor. I'm not sure "normal" people got a glimpse on that side of research, in that field it's actually the biological/chemical experiment that will validate a virtual experiment (remember to watch Terminator 4 or 5 at leas the last on screen...).About the big brain project and graphic cards and evolutionResearch is cool. It's very interesting to see how connections/links between highly specialized fields are happening to build a new framework for research. The big brain project (not sure about the name but there is the US and the EU version) is the perfect example, different fields from neuroscientists to computer graphics and hardware manufacturers need to collaborate to build this virtual brain model.

One of the last comment from the speaker yesterday had a pertinent echo in my head. This comment illustrates perfectly how technology is evolving and frameworks are crossing their paths. He told us that graphic card manufacturer (such as nvidia to not name them) are now developing hardware dedicated to run deep learning process, once again the hardware architecture helping to fasten a programmed algorithm. But until when and is it a good approach?

Years ago and not so long time ago when computers were already getting faster, people were designing hardware to run image processing/computer vision algorithms. This because the computers in their at-this-time state weren't fast enough. Like the brain was too small and needed to grow or modify its physical body to evolve. But then computer became faster and those special design weren't adaptable enough, too specialized. I feel that we are living a similar state with deep learning. The question will be is hyper-specialization of computer hardware the solution - momentarily for sure - for deep learning or not?

About the futureWe are all doomed. Soon computer will be smart enough to redesign their body when they will reach their limits to overpass them. I haven't any spoiler about how and when, out Mayan friends had a big fail about it three years ago, we have to be patient.

16/05/2015

We did it, after 12hours we did it! We went through all normal stages of an impossible bike mission. Small teaser we did follow a kind of a non logical order to do these stages, meaning we first took a lot of breaks and detours and then we started the tour. Also we weren't completely lucky. The tale step by step.

11:37 Lichtenberg train station
The five fantastics are almost all in time for the regional bahn. First detail thousand people with bikes were also in time and the train only have 5 bike places... It's a no go. We change platform and take the S-Bahn until the end to S-Strausberg and decide to do the planned bike tour in reverse mode. The goal once in Strausberg will be to cycle 35km to the Bahn station Obersdorf.

Coffee and bockwurst break in Strausberg
Already 5km (!!!) and first stop in the lovely old Strausberg village tiny burg. Train in Obersdorf is scheduled for 18:39, we have time. We completely deserved this coffee break at Milchbar.

After getting lost in the big city Strausberg while trying to start pursue our soon to be called odyssey we arrive at the lost Pyramide Grazau. Nice little village around and about 15km on the counter. It's also our first detour as leaving the pyramid part of the team decided - unintentional of course - to go toward Ekner which absolutely on the opposite direction of our planned trip.

15:03 picnic at the lac
Back on track we make our first real stop for the picnic. The public beach of Lange See is just for us. Incredible birds are flying around - mostly ducks - and it's a lovely Saturday with friends. Only thing is we started the trip 2hours ago and have done only 20km on the 35km, also some drops are coming.

In the heart of Märkisches Schweiz
The next 15km allows to experience the beautiful region despite the clouds. It's going up and down but completely doable even with shitty bikes. Thanks to our guide tour leader - we call it the PR girl or Anne who is screaming about the beauty of the region while cycling in the middle of the roads with the wind we barely understand what she says but she looks happy so we don't disturb her - we discover more lovely villages.

In Buckow - also called the pearl of the Märkishes Schweiz - the rain shower is a kind of warning: do we continue to Obersdorf under the rain or we go back now to where we start??? We decide to now listen to the sky messages and pursue again our trip.

18:15 Seeing Obersdorf and leaving
The landscape is still lovely and hilly. Three hamlets further full of white and black sheeps we finally reach - in time we thought - our final destination and train station of Obersdorf.

The story is repeating itself, the train is full of bikes and we can't get in...

After strong negotiation between the five fantastics two main ideas arise on the top of the consensus being we go back to Strausberg where we know there will be S-Bahn every 10min, this instead of waiting one hour for the next train still with the chance to not have places, again.

The Obersdorf agreement
First idea is we follow the same way, we know it and it's all along a bike way which is good when we don't have lights on our bikes. Second idea is we take short-cuts by going on roads we don't know with cars on it and we don't have lights... First option is chosen, the reason win, Cartesian spirit for life, on the road again, only 35km remains.

21:12 Strausberg again
A last rush on the platform to change train with bags on our shoulder, open beers in hand and the door closing... But we made it and we are mainly dead.

22/04/2015

Diorama
For the fan of Community, my cake - a modified version of the classic "gateau au yaourt" with blueberries and a tiny bit of coco nuts flakes - with the candles on the top looks pretty much like an attempt of diorama where it would been asked to the students to illustrate the Vesuvius eruption. The cake almost exploded, "a brillé de mille feux" said some people and was delicious.

I swear I'm telling the truth
Alcohol makes you more confident. The proof? Being able to tell in a conversation to an American, a Japanese and a Portuguese that yes there is often big snowstorm in Cap Verde. To help my listeners were also drinking, but at some point I could see the confusion on their faces until I realize that the wrong word was coming out of my mouth. I meant sandstorm but said snowstorm, probably the charm of French people speaking English...

19/04/2015

10:33am wake up with the feeling maybe you drunk one or two beers too much yesterday evening, this despite the good evening. Without a good evening the morning would have been terrible. It was a classic international Friday: meet the spotters from Berlin plus the spotters bosses from Amsterdam plus a visiting spotter from Vilnius and later re-meeting for the first time in 14 years a fellow from Ecole Polytechnique de Montréal and Polyscope. All and all a blast :-)

Some statistic for Friday evening: talked with 10 people, 8 different nationalities. Take that morons.

3:33pm getting some rest in order to give to my body the time to reload before the run. I register for the airport night run in Berlin. They do it regularly and after some years I finally did register, not for the 10km but for the half-marathon.

7:01pm in night run there is night. The half-marathon group starts now and the 10km group one hour later. The feeling you have for this run is pretty cool. The new airport BER is there but empty and you are running on the landing area and tarmac. Two loops to do of 11km something and 10km and the first line is toward the East, the sun is going down, there is nothing miles around you, just some clouds, look to the North and you can see the top of the tv tower and you keep running.

Passing the sign 7km is nice, a third of the run is down! The group is now stretched, I'm running alone, my time after 5km is in my range (below 25min), but sadly I'n not fast enough to keep the same speed of the few jogging babes... my first attempt to drink water without stopping is a big failure as I only manage to spread water in my face.

8:00pm First loop done, meaning for me 11km something in less than an hour, I'm in my time track. As we reach 8:00pm the second group of runners is launched and soon two speed groups are mixing. It's a bit like in zombies movie when a crowd of zombies are all running in the same direction. If you have seen War Z and remember the scene with airplanes chased then it's the same, except there are no planes as the airport is still not open...

8:55pm I'm crossing the arrival line. I'm relieved, less than two hours as I was planning/hoping to do! The temperature is freaking cold, near 4 degrees Celsius only, so fast changing clothes and I leave.

11:04pm S-Bahn, tramway and bike later and I enter the Studios-ID in the middle of Alt-Hohenschönhausen. It's their open studio evening event where I know some the artists (check the website of Kyle Fitzpatrick).

I'm a bit destroyed but I managed to stand on my legs. I talk with many people, once again it's über international, Americans from Miami and Chicago, Russian, German, Portuguese and many more. English, French and German in the same conversation, after my legs it's my brain which is working. And at the question so you are an artist too the response is always or becomes complicated. Well I say, I'm working with color, I'm a color and imaging scientist bla bla bla... but it's usually a good start.

1:04am time to go home, I jump on my bike, 7km to do to reach my bed. The night is fresh but the stars visible. Another full day full of new images in my head.

15/04/2015

In the beginning

What is important to know about machine/deep learning problems? First remark to myself is "what are we trying to solve in general?" and then "which method/technique do we choose?" or "which approach is most appropriate to answer a given problem?".

Optimization for the people

Optimization is widely used to solve complex problems that don't have an analytic expression. But this doesn't mean that problems that have an analytic expression couldn't be solved using optimization.

Optimization relies on a provided model that "model" with reasonable efficiency a phenomenon (e.g. find the colorant combination of cyan, magenta, yellow and more for a give red, green, blue pixel) or anything you want. You may hear about derivatives, gradient, local minimum, cost function, quadratic form, linearity, non-linearity, iteration and more when you start messing around with optimization.

And it's completely possible to use optimization techniques as applied mathematics tools without knowing exactly how they work (e.g. you provide your model and the tools will perform the derivatives for you). In an engineering world you are connecting boxes, each one trying to solve a simple task taking for starting point what the previous is having for output.

Deep learning for the people

Deep learning and neural networks let you do something clever with the way to solve your problem. First of all your problem has been defined and described, but optimization techniques did not provide expected results: it's not fast enough or it's simply not working. One possibility is that your model isn't good enough or way to complex.

The simple idea is to let a system to learn about an ecosystem. To do so we let the algorithms mimicking how our brain is working. The concept of learning is very important here because it is really what we want to achieve. We want that our algorithm learns in a first step by obtaining representative parameters/weights before giving us a result. Then once the learning is finished, for a given entree and with the help of the parameters the algorithm can give us answers. For example is this image an image of a car, an elephant and this with different degrees of confidence.

A big part of the learning is to prepare the training sample. You can't just give images to the algorithm. Applied to computer vision, deep learning methods try to extract features from images in a similar way of how we human recognize information in images. This step of features extraction goes by applying multiple filtering on the images and the resulting filtered images, using convolution and tile approaches. At the end you obtain classes of features and it's very similar to the filters used for face recognition. Only difference is the features that describe a human face are now almost standard and doesn't need to computed or extracted again.

There exist competitions where for a given large database full of images and keywords, people can submit their algorithms. Pretty interesting results are obtained and as in sport faster solutions are appearing often coming with new tools to handle large databases.

Breaking the machine

Hopefully there is always something to improve. Because images can contain more than one object, you could have a bike and an elephant in the same picture. In that case what should reply our algorithm first? There is room for subjectivity here.

These algorithms have to deal with the constant stream of information we are processing, meaning that we are always learning - in theory of course because the world is full of lazy bastards which keeps the marketing and sales people happy making us predictable and therefore easy targets but I digress - and we have to find a way to give this ability to our algorithms or there is the risk for them to over-learn. I really like the metaphor of trying to make an algorithm able to forget part of what he is deep learning to be able to adjust its judgement.

The interesting problems are those that overcome the first limitations encountered. You could try to distinguish what are the elements in a picture (e.g. there is an elephant and a bike) or "simply" give to the image a score. If you take an artist, he will have the tendency not only to make the same picture but to add to its images something that defines the way he perceive the world around him, something pretty unique. A similarity factor or score can be very helpful when you are browsing a large image databases or "just" the internet.

09/04/2015

What was your question already?
How to explain deep learning to your friends, family members, neighbors, random stranger, dog? A very good question indeed. Rather than going deeply into neural networks and other festivities let's start with describing the problem(s) we want to solve. Or least let's give an example of what we are trying to do here.

Over the years I had to come with strategies if I wanted to explain what I do for living. Giving keywords such "color science", "computer vision", "image processing", "digital photography" is usually not enough or saying "I do work with images" neither. I always found interesting to answer the question "why to you want to do that?" or "which problem do you want to solve?". So to explain what I can do I try to give an idea of the tasks I have to solve.

What is the problem you are trying to solve already?
In some way asking these questions is already machine learning/deep learning-ish approach of solving a problem. In theory if someone asks you to solve a problem he knows the kind of results he want to obtain for a given input or starting point. What he doesn't know is what is happening between these two stages. Applied mathematics and optimization are a reasonable standard solution: you develop of model that recreate more-less accurately what is happening between these two stages, then for a new entree point your model will predict what an output will be.

I'm sure "big data" is an expression you have heard in the past years or months. It has of course different meaning depending who to is giving a definition. But, coming back to images and the incredible amount of images we are producing daily there is a need to develop solutions, tools to be able to interact with these images. You have in your hand an extremely large image database and using keyword as a search query isn't enough anymore. So here is the problem: how to navigate, how to browse into large image database in a more natural way? There is a bit of database here but that is not the main point of my article, check my past post on graph and database if you are interested.

Face recognition to recognition of everything
Working with images is fascinating, you see one image and automatically you extract some of its information. Of course there is a long learning curve, when you see a tree, a car, a known object in a picture you don't even realize it, you know, you have learned over the years you spent on earth to recognize, categorize, organize the continuous stream of visual information that come to your eyes and is later processed in your brain.

If you think of face recognition, the mathematical tools are now pretty standard. We can with high probability find out faces in images, classification comes after the recognition. And if you train your model you will be able to recognize semi automatically in a database faces of different persons as the tools/filters can be tuned for a given target. It can be scary of course if the threshold that decide for a true recognition/classification isn't verified by a real human and that action lead to a rocket launch. Actually any automatic action issued from an algorithm decision having impact on a human being is pretty bad (hello mass surveillance and hello Terminator). You want help from robots not to help robots or it's too late anyway.

An idea behind deep learning is to be able to learn what are into images - in a similar way as we human do - to extract features and to perform tasks on other images based on a trained neural network. I'm making shortcuts but that's the idea. To understand and to later mimic how information is circulating into the brain has been a dream of many researchers. Neural networks go into that direction. If a few years ago the algorithms were limited because of computer power the global picture is different now.

What is also interesting is that new strategies had to be developed to overcome the overload of data. In a way the system were "over learning" and people talked about over-fitting the data. And it makes sens. If I'm not too mistaken our brain is not indefinitely expandable, meaning we are sorting information continuously. One big part of these tools is to perform drop-out which can be explained as "now that our system can learn we have to teach him to forget part of what he knows in real time".

Cross disciplines
A chance I see - for me - is the need in some industries for expert being not only expert in one field. Specially for this kind of large scale problems involving images, computer vision, real time and fancy applied research projects. To know only about machine learning or statistic is not enough, to know both about computer and machine learning tools is better.

30/03/2015

Third round in Poland, this time further to the East in the country. A long and full weekend to discover this city, meet my not only Norwegian friends from Oslo and eventually meet locals and/or spotters. It was a good weekend for many reasons putting aside the fact that I was travelling alone. I experienced or entered different layers, networks to get to know this city.

This time I traveled with the Die Welt von Gestern de Stefan Weig which I was reading in French.

I use the public transport, tramways are so cool in Poland.

I made new connections.

I got frustrated to not be able to say more than three words in Polish.

I traveled slow and cheap, train and bus, in total 1000km for a total 82€.

A last full day full of resolution. I crossed the city by tramway, entered its many parks, visited the POLIN Museum of the History of Polish Jews and later in the afternoon met the Oslo team again.

4:00pm we are all waiting for our guide for a scheduled tour of the city. Then he arrives with its old cool mini yellow van. No need to worried about safety belts as there are not safety belts. We just need to relax and grab the red and black fur on the seats to not fall at every turns or bumps on the road.

The path followed by the mini van brought us to many places I have seen the last two days, but the tour guide was entertaining. To conclude our exploration we crossed the river and had a snack in what we can call a witness apartment of old Polish communist time. The vodka was good.

8:08pm despite the aperitif we start looking for a place to have diner and we end up in a kind of semi classic restaurant called Folk Gospoda. To give an image it's all in wood, a bit German style, waiters and waitresses are wearing "traditional" costumes. In comparison to the German version, the waitresses are wearing white socks, semi short skirts revealing her knees but without "décolotté pigeonnant" Bavarian style.

About the food is was way too big, good but way too big, but the beer drinkable. And sadly I could not see the couple making out in the other restaurant room in my back, but at some point two of my friends said "I think the woman on the back is giving an hand job to the guy next to him, noooo" we all said turning synchronously our heads. That was fun.

11.34pm the day isn't over and I left my Norwegian crew at its hotel and continue my city exploration. I have not idea where I'm, but I'm. I met again the Polish and French pair of yesterday with more Polish people. A very nice end of my short trip in Warsaw. I never thought this trip will have ended up with a long and passionate discussion about color imaging and ACES, but life is full a surprises.

I will have to go to bed at some point, my Polskybus is leaving the city in a few hours.

29/03/2015

11:01am early awake but later than yesterday! A short look into my spotted by local app and decide for an hummus breakfast. Then I aim for the sky, go toward the Palac Kultury, got lost in the building and finally find the elevator. The view once almost on the top of the building is stunning. I can see where I went yesterday and can locate where I had my delicious hummus and halloumi burger some minutes ago in Beirut.

Back on earth I enter the nearby located Museum of Modern Art. It's squeezed between towers but you don't feel compressed once inside. If you like poster and book shop, that's the place to go.

4:04pm second try for the planetarium, I failed but I successfully acquired some bike accessories in antymateria. At the question from one of the shop crew member "how did you find out about our shop already?", "well" I answer, "I'm coming from Berlin, know some shops there, asked there if they know people in Warsaw, then I talked on the net with shared connection being a frame builder in Warsaw that recommended some addresses and here I'm!" thanks to the bike messenger communities in the different cities I thought.

8:03pm I meet my Scandinavian crew in a Polish posh restaurant - as will later describe our tour guide the next day. I lost some money on that game but I kept my clothes, so the honor is safe. Being a bit ill at a fancy restaurant is problematic as everything taste the same, color and texture are changing but still you don't get the full experience. Anyway...

11:33pm a drink at a panorama bar in the city center and we split the group. At that time I thought I already entered a parallel world while having diner in the previous restaurant - the Belevedere - but I was wrong. There are many parallel universes or many ways to explore cities or interact with new spaces, I explain in the following lines.

It's passed midnight and I'm meeting a French journalist - also writer for spotted by locals, not for Warsaw but Budapest. Thanks to the internet I got to know during the day that she was visiting Warsaw and a Polish friend this weekend. Where do we meet she asked? I checked on my foursquare, found out some places recommended by Lithuanian friend - other spotter from Vilnius this time, I met him in Berlin in Amsterdam. So here we are, three people, one true local and two local travelers having a last Saturday drink in Kraken. Funny because at the beginning of my day I had not idea I will conclude my path in the same place I started - the hummus place and this bar share the same address.

3:33am late again but I got a lift home to my beloved Campanile hotel. Another full day.

27/03/2015

6:15am and I'm on the platform at the Berlin Hauptbahnhof. As opposed to the train driver the other travelers and me are in time. Luckily the train - the Warsaw Express where Express has nothing to do with the speed - being not full means you can seat comfortably and enjoy the long ride to Warsaw.

2:04pm I leave the train station, elevator and bamm I have in front of me the Palac Kultury. I blink my eyes, nooo am I in New-York or what? No, I'm in Poland. 900m further I enter my hotel room located nearby the Warsaw central station. A shower and I'm ready to explore the city. My phone is fully charged, my spotted by local city guide for Warsaw up to date, let's go!

One pass for the public transport in my pocket, I jump in a bus direction the Copernicus Science Center, I heard often about this place during my last job, despite the relative short distance to Berlin I never managed to visit it.

My phone indicates me a 20min bus ride but I left my coach before my final destination, I have seen a bike shop in the street... I meant that one Rowery Bajery. I talk a bit with the owner and manage to leave without buying a bike. A crêpe in Rue de Paris and I finally reach the science center.

4:47pm I pay my entree for the science museum. It's Friday, full of kids from the school running around. I guess the only difference with a weekend day will be more parents in zombie mode with kids running around. But the place is a giant playground for who wants to play with science and get introduction to basic concepts, installations are working, many experiments are doable, friendly staff.

On my way back to my hotel I locate more bike shops - thanks to the local tips I gather before leaving Berlin - but I remain strong and only ask for prices. The street is going up, bike shops, music shops and sometimes bar and bike shop together, an awaken dream this city.

Getting close to a large avenue I spot the palm tree. To me a very good integration of urbanity and modern art. First surprising and then finding it completely in harmony with the roundabout, the cars, the bus, the tramways and buildings.

8:11pm evening is coming and I meet a Morten, a Norwegian scout - but also a friend - here some hours in advance to prepare the field for more Scandinavians. Always nice to meet the friends from other places in other places.

10:11pm the rest of the troop is finally arriving and we all go to the Bazard Klub. The place looks fine, but arriving late together with the staff members we are the only not drunk people.

Then it's time to go sleeping, I'm awake for way to long today. On the way back to our hotels I'm the last leaving the taxi. I continue alone the discussion with the driver, in English - because my Polish sucks - even so it could have been in German. He told me his grand mother used to leave in Berlin not far from where I live.